The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Image thresholding considered as a popular method for image segmentation. So far, many approaches have been proposed for image thresholding. Maximum entropy thresholding has been widely applied in the literature. This paper proposes a multilevel image thresholding (MECOAT) using cuckoo optimization algorithm (COA). COA is a new nature- based optimization algorithm which is inspired by a bird named...
Mass segmentation in mammograms is a challenging task if the mass is located in a local dense background. It can be due to the similarity of intensities between the overlapped normal dense breast tissue and mass. In this paper, a self- adjusted mammogram contrast enhancement solution called Adaptive Clip Limit CLAHE (ACL-CLAHE) is developed, aiming to improve mass segmentation in dense regions of...
This paper presents an improved discrete quantum particle swarm optimization (IDQPSO) for 2-D maximum entropic multi-threshold image segmentation algorithm. Firstly, particle swarm binary-encoded method based on 2-D threshold is proposed. Additionally, new particle evolution strategy is proposed to avoid converging on local optimum and accelerate searching progress. Additionally, experiments are conducted...
Robust and automatic segmentation of the neighboring cells remains a challenging problem due to the diversity of the cell types, frequently occurring artifacts, weak borders between adjacent cells, the arbitrary shape and large number of cells. Currently, the widely used segmentation and quantification tools are still manual or semi-automatic, which is time-consuming and labor intensive. With a breakthrough...
Over the past years, Electrocardiogram (ECG) as a biometric characteristic, has been investigated in several works. The human heart is physiologically a liveness indicator. Feasibility of continuous signal acquisition and demonstration of subject aliveness, are the most important properties of ECG based authentication systems which makes them different from common authentication methods like fingerprints...
In this paper, the problem of segmenting images with nonuniform lighting conditions has been addressed. It has been observed that for such images homogeneous granulation based thresholding algorithms yields poor results. In order to deal with such images, the notion of adaptive windowing has been employed using the notion of window growing. The windows have been fixed based on the entropy measure...
This paper addresses the thresholding of biological images through multiobjective optimization techniques. Three objective functions are used during the optimization, which are combined at pairs: Shannon entropy versus Otsu's inter-class and Shannon entropy versus Otsu's intra-class. We show that although both combinations are obtaining the same vector of thresholds, the first objective function pair...
Due to some tiny structures and blurred boundaries of retinal vessels, especially with the low illumination contrast and strong noise resulted from retinal image collecting, it is difficult to automatically extract vessels from retinal images. In this paper, a novel automatic extraction algorithm for retinal vessels is proposed. Firstly, a non-uniform illumination correction method is used together...
Diabetic retinopathy (DR) is a complication of retinal related common micro vascular disease occurred in diabetic patients. It is the one of the major causes of adult blindness in the worldwide. DR is indicated by the presence of hard exudates, soft exudates, haemorrhages, the growth of new blood vessels and foveal avascular zone (FAZ) enlargement. The objective of this work is to detect FAZ area...
Spectral clustering employs spectral-graph structure of a similarity matrix to partition data into disjoint meaningful groups, because of its well-defined mathematical framework, good performance and simplicity, spectral clustering has gained considerable attentions in the recent past. Despite these virtues, it suffers from several drawbacks, such as it is unable to determine a reasonable cluster...
Medical image segmentation is always the hot topic of medical image analysis. Due to the images' complex topological changes, high noise and lower contrast, one-dimensional histogram based classical thresholding segmentation methods are always helpless. Therefore, 2D histogram-based image segmentation methods have been gradually became the issue of image segmentation. Since basic GA based 2D maximum...
In the field of neuropsychiatrie disorders, it is known that brain segmentation is important for both detection and diagnosis. The segmentation of the brain, which leads to the computation of brain volume proved to be vital in the detection of many brain pathology having Computed Tomography (CT) scan as the primary modality. Due to the fact that Fuzzy c-Means (FCM) proven to be robust, it is often...
In order to improve the accuracy of medical image segmentation and overcome the shortcomings of maximum entropy segmentation algorithm, the paper proposes the medical image segmentation based on maximum entropy multi-threshold segmentation optimized by improved cuckoo search algorithm (MCS). Firstly, the maximum entropy method is adopted to find the optimization objective function, then the improved...
To provide tools for image understanding, non-trivial task of image segmentation is now put on a new semantic level of object detection. Internal, external and contextual region properties often can adequately represent image content but there arises field of view coverings. Truthful image interpretation strictly depends on valid number of regions. The goal is an attempt to solve image clustering...
The image thresholding approach based on the basis of 2-D maximum entropy has better segmentation performance by the use of local space information of pixels, but it is unpractical for heavy computation required by this method. In the paper, an image segmentation technology based on cuckoo search and 2-D maximum entropy is presented, which views the seeking of 2-D maximum entropy of the image as a...
The main idea of this paper is to adapt the Artificial Bee Colony metaheuristic to solve the problem of multilevel thresholding for image segmentation. More precisely, this method is exploited to optimize two maximizing functions namely the between-class variance (the Otsu's function) and the entropy thresholding (the Kapur's function). This leads, respectively, to two versions of the ABC metaheuristic:...
Prediction of performance in Off-line Automatic Signature Verification (ASV) per signer is one of the important topics regarding to automatic verification. It could be hypothesized that the performance of a signer is related to its global stability. This way, the more stable the signer signatures, the smaller the area of its feature space is, being more difficult to get inside for an impostor. In...
This paper discusses about a method adopted to develop a computer-aided diagnostic system to achieve automatic detection and classification of liver lesions. The procedure followed consists of first segmenting the CT scan image so as to accurately extract out the lesion region alone from the rest of the abdominal details. This Region Of Interest(ROI) is now used up for extracting out first order and...
Diabetes mellitus is a major disease spread all across the globe. Long-time diabetes mellitus causes the complication in the retina called Diabetic Retinopathy (DR), which results in visual loss and sometimes blindness. In this paper, we discuss a simple and effective algorithm for segmentation of the optic disk (OD) and bright lesions such as hard exudates from color retinal images. Color fundus...
Cyclone vortex localization under varying conditions of saturated spiral bands is challenging. This paper presents a unique combination of image processing techniques, viz., Sequential Cross-Correlation (SCC) and Multi-Level Thresholding (MLT) for vortex localization. SCC is used for cyclone detection in a full-disk satellite imagery, and is based on the high degree of correlation in the sequence...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.